TY - JOUR
T1 - Robust atrophy rate measurement in Alzheimer's disease using multi-site serial MRI
T2 - Tissue-specific intensity normalization and parameter selection
AU - Leung, Kelvin K.
AU - Clarkson, Matthew J.
AU - Bartlett, Jonathan W.
AU - Clegg, Shona
AU - Jack, Clifford R.
AU - Weiner, Michael W.
AU - Fox, Nick C.
AU - Ourselin, Sébastien
N1 - Funding Information:
The authors would like to thank Josephine Barnes at the Dementia Research Centre, and Derek L.G. Hill and David M. Cash at IXICO for helpful discussions. We would also like to thank all the image analysts (Melanie Blair, Magda Sokolska, Elizabeth Gordon, Raivo Kittus, Laila Ahsan, Kate MacDonald) and the research associates (Casper Nielsen and Ian Malone) in the Dementia Research Centre for their help in the study. The implementation of KN-BSI uses the Insight Segmentation and Registration Toolkit (ITK), an open source software developed as an initiative of the U.S. National Library of Medicine and available at www.itk.org . Data collection and sharing for this project were funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI; Principal Investigator: Michael Weiner; NIH grant U01 AG024904 ). The Foundation for the National Institutes of Health ( www.fnih.org ) coordinates the private sector participation of the $60 million ADNI public–private partnership that was begun by the National Institute on Aging (NIA) and supported by the National Institutes of Health. To date, more than $27 million has been provided to the Foundation for NIH by Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly and Co., Merck & Co., Inc., Novartis AG, Pfizer Inc., F. Hoffmann-La Roche, Schering-Plough, Synarc Inc., and Wyeth, as well as non-profit partners the Alzheimer's Association and the Institute for the Study of Aging. This work was undertaken at UCL/UCLH which received a proportion of funding from the Department of Health's NIHR Biomedical Research Centres funding scheme. The Dementia Research Centre is an Alzheimer's Research Trust Co-ordinating centre. K.K.L. and M.C. are supported by a Technology Strategy Board grant ( TP1638A ), N.C.F. is funded by the Medical Research Council (UK). The authors would particularly like to thank the ADNI study subjects and investigators for their participation.
PY - 2010
Y1 - 2010
N2 - We describe an improved method of measuring brain atrophy rates from serial MRI for multi-site imaging studies of Alzheimer's disease (AD). The method (referred to as KN-BSI) improves an existing brain atrophy measurement technique-the boundary shift integral (classic-BSI), by performing tissue-specific intensity normalization and parameter selection. We applied KN-BSI to measure brain atrophy rates of 200 normal and 141 AD subjects using baseline and 1-year MRI scans downloaded from the Alzheimer's Disease Neuroimaging Initiative database. Baseline and repeat images were reviewed as pairs by expert raters and given quality scores. Including all image pairs, regardless of quality score, mean KN-BSI atrophy rates were 0.09% higher (95% CI 0.03% to 0.16%, p=0.007) than classic-BSI rates in controls and 0.07% higher (-0.01% to 0.16%, p=0.07) higher in ADs. The SD of the KN-BSI rates was 22% lower (15% to 29%, pb0.001) in controls and 13% lower (6% to 20%, p=0.001) in ADs, compared to classic-BSI. Using these results, the estimated sample size (needed per treatment arm) for a hypothetical trial of a treatment for AD (80% power, 5% significance to detect a 25% reduction in atrophy rate) would be reduced from 120 to 81 (a 32% reduction, 95% CI=18% to 45%, pb0.001) when using KN-BSI instead of classic-BSI. We concluded that KN-BSI offers more robust brain atrophy measurement than classic-BSI and substantially reduces sample sizes needed in clinical trials.
AB - We describe an improved method of measuring brain atrophy rates from serial MRI for multi-site imaging studies of Alzheimer's disease (AD). The method (referred to as KN-BSI) improves an existing brain atrophy measurement technique-the boundary shift integral (classic-BSI), by performing tissue-specific intensity normalization and parameter selection. We applied KN-BSI to measure brain atrophy rates of 200 normal and 141 AD subjects using baseline and 1-year MRI scans downloaded from the Alzheimer's Disease Neuroimaging Initiative database. Baseline and repeat images were reviewed as pairs by expert raters and given quality scores. Including all image pairs, regardless of quality score, mean KN-BSI atrophy rates were 0.09% higher (95% CI 0.03% to 0.16%, p=0.007) than classic-BSI rates in controls and 0.07% higher (-0.01% to 0.16%, p=0.07) higher in ADs. The SD of the KN-BSI rates was 22% lower (15% to 29%, pb0.001) in controls and 13% lower (6% to 20%, p=0.001) in ADs, compared to classic-BSI. Using these results, the estimated sample size (needed per treatment arm) for a hypothetical trial of a treatment for AD (80% power, 5% significance to detect a 25% reduction in atrophy rate) would be reduced from 120 to 81 (a 32% reduction, 95% CI=18% to 45%, pb0.001) when using KN-BSI instead of classic-BSI. We concluded that KN-BSI offers more robust brain atrophy measurement than classic-BSI and substantially reduces sample sizes needed in clinical trials.
KW - Alzheimer's disease
KW - Atrophy
KW - BSI
KW - Boundary shift integral
KW - Intensity normalization
KW - KN-BSI
KW - MRI
UR - http://www.scopus.com/inward/record.url?scp=77952314159&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952314159&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2009.12.059
DO - 10.1016/j.neuroimage.2009.12.059
M3 - Article
C2 - 20034579
AN - SCOPUS:77952314159
SN - 1053-8119
VL - 50
SP - 516
EP - 523
JO - NeuroImage
JF - NeuroImage
IS - 2
ER -